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Security harness for AI coding agents (Claude Code, Codex CLI, etc.) — mitmproxy payload inspection + TOML policy control.

Trace capture for Claude Code sessions - sync to Pisama platform for analysis

Native macOS GUI for the Hermes AI agent — multi-window, multi-server (local + remote over SSH). Chat, dashboard, sessions, memory, cron, MCP, and more.

Orchestrate local LLMs across devices with no cloud dependency

Top AI Multi-Agent Memory Systems 2026 🚀 | Next-Gen Embodied AI Evolution Tools & Resources

雷神 Raijin — the terminal-first Agentic Development Environment. Built in Rust on our own GPU UI framework (Inazuma). World-first: per-command GPU block grids, native Nushell structured output, and TUI-aware block rendering. 97 context chips and 715 CLI completions built into the binary. Zero plugins. Zero compromises.

AI-first Go framework for building internal tools and background jobs — just prompt, AI does the rest.

An open-source terminal coding agent runtime and CLI for real project work.

Slack for humans + AI agents — ships with OpenClaw & Nanobot channels. Self-hosted, pip-installable, no Redis.

LLM agents for Odin, built on the actod actor runtime.

DolphinDB Agent Skills installer — install DolphinDB knowledge skills into your AI coding agent (Claude Code, Cursor, Trae, etc.)

Agent-native CLI for Naver Open APIs

An "LLM wiki" upgraded to a real database — typed entities, graph relations, HTTP API, and a built-in natural-language agent.

The AI agent with a wallet — spends USDC autonomously to get real work done. Apache-2.0, TypeScript.

Unified Python interface for invoking AI coding-agent CLIs (claude-code, opencode, codex, gemini, aider, swe-agent) as subprocesses.

Multi-agent consensus protocol — weave votes into fleet decisions with quorum and veto

A pip-installable CLI that scaffolds a learning-environment folder for any LLM agent to operate as an adaptive mentor.

Dynamic Consensus System — multi-agent belief, lock accumulation, consensus

Turn successful AI agent runs into reusable markdown skills

Operating rules for LLM coding agents — reduces silent assumptions, overbuilding, scope creep, contract breaks, premature optimization, fake verification, and unsupervised output